According to the Chartered Institute of Marketing, four in five marketers now believe experience to be a stronger driver of brand performance than communications. As AI and voice user interfaces (VUIs) become widely adopted in people’s homes, the experiences brands can deliver will become much more personalised, and therefore more likely to lead to action.

The rise of Google, Amazon and Apple voice assistants in people’s homes is making great strides in establishing the voice interface as an accepted long-term replacement for screens, mice and keyboards. This applies out of the home too. While the thought of publicly saying ‘OK Google’ into your phone might bring the average Brit out in a cold sweat, nonetheless 37 per cent of smartphone users do use voice technology of some kind to converse with their device at least once a month. By 2020 50 per cent of all searches are forecast to be made using voice.

But as Robert Swhwartz, VP global digital marketing at IBM, said: "It’s one thing to redesign a digital experience, or makeover a website or app, but it’s quite another to add the power of thinking and cognitive computing into embedded experiences."

Much of the commentary about AI envisages it replacing humans. But more thoughtful analysis acknowledges that there are some roles humans are uniquely adept at. The challenge for brands then is to use AI to augment the human aspects of brand experience. Here are five ways brands can harness AI to create personalised and meaningful experiences for customers:

1. Learn through play

Voice can provide a playful experiential interface, through which complex information and stories can be understood. IKEA’s innovation lab Space 10 utilised voice to do exactly that as part of London Design Week. A tactile pop-up invited visitors to learn about Lokal’s aquaponics system as part of their ‘future of living’ series.

The space was devoid of text or video content, all the experience involved was a Google Home, a greenhouse and some hands-on implements. Through conversation, visitors were prompted by the voice assistant to conduct various tasks, resulting in a clear explanation of the processes of aquaponics and urban-space horticulture.

2. Using voice ‘skills’ and ‘actions’ to create controlled environments

Google Assistant and Amazon Alexa both host third-party ‘actions’ or ‘skills’ which function much like apps but over a VUI. Amazon has also made Alexa available to hardware developers in an attempt to stimulate the market. For brands, this means contained conversations can be created, without the possibility of users veering off into the abyss of the rest of the internet. Dominos voice assistant Dom and Johnny Walker’s voice assisted whisky tastings are both early examples of useful conversational consumer experiences.

3. Understanding audiences

We live in a world where data, insight and understanding the audience is paramount. We’ve built intricate systems that capture feedback but understanding people’s perceptions at free will, via conversation, opens up a new, honesty-based field of data collection and audience understanding.

4. A single conversational engine with multiple interfaces

Despite the current duopoly of Google and Amazon, AI-powered voice and text interfaces will continue to proliferate. But as the AI-powered conversation landscape fragments, brands building skills and apps run the risk of wasting time rebuilding for different systems. This has led to the development of ‘unified conversational engines’ like Dialogflow. These back-end conversation management systems mean that one single app can be built, managed and implemented through any platform and across devices.

5. Supercharging CRM

Building an ongoing and meaningful relationship with customers beyond their experiences has proved tricky for many brands. Large-scale customer data collection and tailored communications programmes have existed for a long time.

But by embedding machine learning enabled chat and voice interfaces into experiences, huge amounts of data can be collected. There is great potential to transform customer and employee experiences to be not only responsive and personalised, but also predictive.

Machine learning means that natural language processing and speech recognition are always improving. When they are plugged in to experiences and combined with an always-on collection of data detailing behaviours, preferences and emotions, these experiences can self-learn and improve too.

Much has been written on the impact of AI, voice and chatbots on the digital customer journey, but brands that can create a consistent always-on conversation that comes to life physically and digitally will transcend devices and single interfaces.

Considering we now live in an age where toddlers swipe fruitlessly at magazines and call them ‘broken iPads’, and museum and trade show visitors assume every screen they encounter to be a touchscreen, any three-dimensional space that doesn’t react to visitors and serve up relevant, personalised content will be dismissed as not worth the time.